Investigation and development of new concepts for improvement of aircraft electrical power systems Quarterly progress report

Aircraft electrical power systems optimizatio

Sähkönsiirtoverkko-omaisuuden kunnonvalvontajärjestelmä Esineiden Internet -alustalla

Fingrid is making the transition from time-based maintenance to condition-based maintenance in order to increase the cost-efficiency of substation asset condition management and to prevent equipment failures. Digitalization improves real-time visibility to asset condition as Fingrid is developing an Internet of Things (IoT) concept for online asset condition monitoring. The objective of this Thesis was to specify Fingrid's requirements for asset condition data visualization in an Asset Performance Management (APM) application. A secondary objective was to document Fingrid's IoT concept and existing condition monitoring practices. Asset maintenance strategies, digitalization and Internet of Things were discussed as a background. For the IoT data of switchgear, simple illustrations of dashboards were drawn to show how the data could be visualized in an APM application. Regarding power transformers, the necessary basic elements for condition data visualization were reviewed. Specifications for visualization of all the available condition data were listed in Appendices. Online condition monitoring is currently concentrated on switchgear, power transformers and substation buildings. The IoT solution for switchgear consists of low-cost sensor units installed in switchgear control cabinets and bay marshalling cabinets. Power transformers are equipped with online DGA (Dissolved Gas Analysis) instruments which is a well-established practice. In substation buildings, the climate is monitored with low-cost IoT sensors. The conclusion of the study was that there are two types of condition data that determine Fingrid's requirements for data visualization in an APM application: time series data and event data. Monitoring of continuous processes produces a large amount of continuous time series data. A tool with efficient functionalities for time series data presentation and analysis is needed. Switchgear operations and oil sampling produce event data that require visualization in forms of data reporting and special analyses. The amount of event data is small even though it will increase due to IoT.Fingrid on siirtymässä aikaperusteisesta sähköasemien kunnossapidosta kuntoperusteiseen kunnossapitoon kustannustehokkuuden parantamiseksi ja laitevikojen ennalta ehkäisemiseksi. Reaaliaikaista näkyvyyttä omaisuuden kuntoon parannetaan kehittämällä "Esineiden Internet" (\textit{engl. Internet of Things, IoT}) -konsepti omaisuuden käytönaikaiseen kunnonvalvontaan. Tämän diplomityön tavoitteena oli laatia määrittelyt kunnonvalvontadatan visualisoinnille omaisuuden kunnonvalvontajärjestelmässä. Toisena tavoitteena oli dokumentoida Fingridin IoT-konsepti ja käytössä olevat perinteiset kunnonvalvontamenetelmät. Taustana työlle esiteltiin omaisuuden kunnonhallintamalleja, digitalisaatiota ja Esineiden Internetiä. Kytkinlaitteiden IoT-datan visualisoinnin tarpeiden hahmottamiseksi laadittiin luonnoksia kunnonvalvontajärjestelmän näkymistä. Muuntajien kunnonvalvonnan tarpeelliset osa-alueet kunnonvalvontajärjestelmässä käytiin läpi käytössä olevia ratkaisuja tutkimalla. Määrittelyt kaiken käytettävissä olevan kunnonvalvontadatan visualisoinnille listattiin työn liitteissä. Käytönaikainen kunnonvalvonta keskittyy tällä hetkellä kytkinlaitteisiin, muuntajiin ja sähköasemarakennuksiin. Kytkinlaitteiden IoT-ratkaisu koostuu kytkinlaitteen ohjainkaappiin sekä kytkinkentän jakokaappiin asennetuista kustannustehokkaista sensoriyksiköistä. Muuntajat on varustettu jatkuva-aikaisella vikakaasujen seurannalla, mikä on toimivaksi todettu ja vakiintunut kunnonvalvontamenetelmä. Asemarakennusten olosuhteita valvotaan huoneisiin sijoitetuilla IoT-sensoriyksiköillä. Työn johtopäätöksenä voidaan todeta kunnonvalvontadatan jakaantuvan pääasiassa kahteen muotoon, jotka määrittelevät Fingridin tarpeet kunnonvalvontajärjestelmälle. Jatkuva-aikaisten prosessien valvonta tuottaa suuren määrän jatkuvaa aikasarjadataa, minkä vuoksi tehokkaat työkalut aikasarjadatan esittämiselle ovat tarpeen. Kytkinlaitteiden ohjaukset ja muuntajien öljynäytteet puolestaan tuottavat tapahtumaperusteista dataa, jonka visualisointi muistuttaa datan raportointimenetelmiä. Tarvitaan erilaisia datan esitystapoja ja mukautettuja analysointimenetelmiä. Tapahtumadatan määrä on pieni siitä huolimatta, että sen määrä kasvaa huomattavasti IoT:n myötä

Integrated monitoring and control for intelligent power substations

Power substations can be considered the major component of an electric power transmission system, influencing the reliability, security and efficiency of all functions of the system. The idea of "intelligent sub-stations" is the main theme of this thesis. First of all, a distributed monitoring system was developed so that the concept of sub-station automation could be realised. The monitoring system was successful in interfacing all major components inside a sub-station using simple hardware and off-the-shelf personal computers. This system formed the foundation of all subsequent research work described in this thesis. It was further developed to possess two outstanding functions, namely computer vision and Internet access. Using computer vision, the human operators in the central control centre were able to get the full picture of what happened in the sub-station with full confidence under a real-time mode. With Internet access, relevant information could be made available to all personnel concerned with the normal operation and maintenance and ad hoc emergency fault attendance as well. With this basic hardware and software being successfully implemented in three sub-stations in Hong Kong, advanced features involving techniques in artificial intelligence were employed for enhancing the existing functions of the distributed monitoring system. Fuzzy logic was extensively applied for reactive power control and power harmonics signature recognition. The response and accuracy of reactive power control which was so important in maintaining a constant voltage level of the power system could be improved. With power harmonics signature recognition, the concept of power quality control could be realised as this problem was getting more and more serious as power electronics equipment was extensively utilised. Artificial neural networks were employed to evaluate the harmonics spectra of the power line, which could be a useful partner to the fuzzy system. The fundamental frequency could be evaluated on a real-time basis. The artificial neural networks were extended from the conventional real space into the complex space which saw great application in power system analysis. Finally, evolutionary programming was used to estimate the parameters of rotating machines during the state of transient operation. With the modem field oriented control strategy, accurate parameter estimation was more and more demanding. Further to that, parameter estimation could be a useful aid to the policy of condition based maintenance which was widely used in the power industry. As future research work, preliminary studies on the application of thermography in power sub-stations and virtual reality were carried out. A brief report on these studies is included in the concluding chapter. As a final remark, the systems described in this thesis may also be useful to aid the successful implementation of the policy of deregulation of power systems in the future

Volume 2 – Conference: Wednesday, March 9

10. Internationales Fluidtechnisches Kolloquium:Group 1 | 2: Novel System Structures Group 3 | 5: Pumps Group 4: Thermal Behaviour Group 6: Industrial Hydraulic

Evaluation of a fuzzy-expert system for fault diagnosis in power systems

A major problem with alarm processing and fault diagnosis in power systems is the reliance on the circuit alarm status. If there is too much information available and the time of arrival of the information is random due to weather conditions etc., the alarm activity is not easily interpreted by system operators. In respect of these problems, this thesis sets out the work that has been carried out to design and evaluate a diagnostic tool which assists power system operators during a heavy period of alarm activity in condition monitoring. The aim of employing this diagnostic tool is to monitor and raise uncertain alarm information for the system operators, which serves a proposed solution for restoring such faults. The diagnostic system uses elements of AI namely expert systems, and fuzzy logic that incorporate abductive reasoning. The objective of employing abductive reasoning is to optimise an interpretation of Supervisory Control and Data Acquisition (SCADA) based uncertain messages when the SCADA based messages are not satisfied with simple logic alone. The method consists of object-oriented programming, which demonstrates reusability, polymorphism, and readability. The principle behind employing objectoriented techniques is to provide better insights and solutions compared to conventional artificial intelligence (Al) programming languages. The characteristics of this work involve the development and evaluation of a fuzzy-expert system which tries to optimise the uncertainty in the 16-lines 12-bus sample power system. The performance of employing this diagnostic tool is assessed based on consistent data acquisition, readability, adaptability, and maintainability on a PC. This diagnostic tool enables operators to control and present more appropriate interpretations effectively rather than a mathematical based precise fault identification when the mathematical modelling fails and the period of alarm activity is high. This research contributes to the field of power system control, in particular Scottish Hydro-Electric PLC has shown interest and supplied all the necessary information and data. The AI based power system is presented as a sample application of Scottish Hydro-Electric and KEPCO (Korea Electric Power Corporation)

Analyse et évaluation de l’application du cadenassage sur des machines dans des entreprises du Québec

RÉSUMÉ : De nombreux décès et accidents surviennent lors des interventions de maintenance sur des machines industrielles. L’automatisation et la mécanisation du travail ont tendance à réduire le nombre d’opérateurs de machines. Les interventions de maintenance demeurent souvent complexes et dangereuses. La maintenance étant souvent négligée par les concepteurs de machines, plusieurs risques résiduels associés aux interventions de maintenance sur des machines doivent être gérés par les utilisateurs en entreprises. Par ailleurs, compte tenu des risques associés à la réparation et l’entretien des machines, la plupart des législations des pays industrialisés, incluant le Canada, font référence à une méthode de réduction du risque, notamment au cadenassage (consignation ou lockout) des équipements. Au Canada, de nombreux accidents sont causés par l’absence ou des lacunes au niveau du cadenassage. La norme canadienne CSA Z460-13 prescrit des exigences relatives à la maîtrise des énergies dangereuses associées à des machines. La norme CSA Z460-13 définie le cadenassage comme une méthode ou une procédure de cadenassage qui consiste en l’installation d’un cadenas ou d’une étiquette sur un dispositif d’isolement des sources d’énergie conformément à une procédure établie, indiquant que le dispositif d’isolement des sources d’énergie ne doit pas être actionné avant le retrait du cadenas ou de l’étiquette conformément à une procédure établie. En 2016, la Commission des Normes, de l’Équité, de la Santé et de la Sécurité du Travail (CNESST) a révélé que en moyenne 4 décès et 1 000 accidents par an sont causés par le dégagement intempestif d’une source d’énergie lors de travaux d’installation, d’entretien ou de réparation sur des machines mal ou non cadenassées (consignées). Dans cette thèse, les observations ont eu lieu dans le secteur des scieries et les résultats des observations de l’application des procédures (57), d’entrevues semi-dirigées (22) et de la documentation sont présentés et analysés. Cette étude a permis de comparer l’application en usine et les prescriptions normatives et règlementaires. En effet, l’application réelle du cadenassage diffère des écrits de l’usine, des normes et du règlement dans les entreprises visitées. Les résultats de la recherche montrent que: (i) les procédures (fiches de cadenassage) ne sont presque pas utilisées lorsqu’il y a 2 sources et moins d’énergie, (ii) les fiches de cadenassage observées ne sont pas conformes aux exigences règlementaires et normatives, (iii) les méthodes de cadenassage varient d’une entreprise à l’autre, malgré des exigences normatives qui proposent un cadre précis commun, (iv) les autres méthodes de maîtrise des énergies dangereuses sont utilisées sans effectuer d’analyse du risque, (v) des entreprises peuvent appliquer des procédures de cadenassage sans avoir de programme pour l’encadrer, (vi) les programmes écrits ne reflètent pas la réalité observée lors de leur application, (vii) les alternatives aux méthodes de contrôle des énergies sont différentes de celles proposées dans les normes, (viii) les difficultés et des facteurs favorisants lors du cadenassage, tels que le rapprochement des points d’isolement de la zone dangereuse, la simplification du cadenassage ou la vérification de la zone dangereuse avant le démarrage de la machine permettent d’améliorer l’application, (ix) une faible vérification d’absence de l’énergie effectuée par les travailleurs et (x) un système de validation d’absence de l’énergie à l’aide d’un système de contrôle dédié à la sécurité renforce l’application d’une procédure. Le domaine du cadenassage est en pleine évolution au Québec en 2016 avec des nouveaux articles scientifiques et un nouveau règlement en santé et en sécurité du travail. Cette thèse est la première recherche sur l’observation directe du cadenassage en entreprises.----------ABSTRACT : In Canada and other industrialized countries, workers who have to intervene in hazardous zones during machinery maintenance, repair or unjamming must apply lockout/tagout or other energy-controlling procedures. Canadian Standard CSA Z460 defines lockout as the installation of a lock or tag on an energy-isolating device on machinery in accordance with an established procedure. Activation of the energy-isolating device must only be possible after the previously applied lock or tag has been removed in accordance with the established procedure. The steps in the lockout procedure are: (i) turning off the equipment, (ii) isolating the energy sources, (iii) de-energizing the energy sources, (iv) dissipating residual energy, and (v) verifying that the equipment is actually at zero energy. However, multiple questions remain about the lockout concept and the related regulatory requirements. In 2016, the Commission des normes, de l’équité, de la santé et de la sécurité du travail (CNESST) revealed that an average of four deaths and 1,000 accidents are caused annually by the inadvertent start-up of an energy source during the installation, maintenance or repair of machinery that is not properly locked/tagged out or not locked/tagged out at all. The aim of the current study was to analyze and evaluate the application of lockout programs and procedures on machinery. The observations documented in this thesis were carried out in the wood processing industry. The thesis presents and analyzes the results of the 57 sessions during which the application of procedures was observed in the sawmills and of the 22 semi-structured interviews, as well as the programs collected. The study revealed a major gap between the application of lockout procedures and programs in sawmills and the normative and regulatory requirements. In fact, the actual application in the visited companies differed greatly from the written programs, standards and regulations. The research findings were as follows: (i) procedures (lockout placards) were essentially not followed when there were two sources and less of energy, (ii) the lockout placards observed were not compliant with the regulatory and normative requirements, (iii) lockout procedures varied from one company to another despite normative requirements that advocate a specific common framework, (iv) other methods of controlling hazardous energies were used without performing risk analysis, (v) one company applied a lockout procedure with no program to guide it, (vi) the written programs did not reflect the realities observed during their application, (vii) the alternative methods used to control hazardous energies were different from those proposed in the standards, (viii) the identification of problems hindering and factors facilitating lockout, such as bringing isolation points closer to the hazardous zone, simplifying the lockout procedure or verifying the hazardous zone prior to starting up the machinery, led to adaptations and improved lockout procedures, (ix) the workers performed little verification of the zero-energy state, and (x) the introduction of a safety-dedicated control system for validating zero energy strengthened application of the procedure. The issue of lockout is currently undergoing considerable change, with the arrival of new scientific articles and the new Quebec regulation in 2016. This thesis documents the first study based on direct observations of lockout procedures in companies

Forecasting Wind Turbine Failures and Associated Costs

Electricity demand is rapidly increasing with growth of population, development of technologies and electrically intensive industries. Also, emerging climate change concerns compel governments to seek environmentally friendly ways to produce electricity such as wind energy systems. In 2018, the wind energy reached 600 GW total capacity globally. However, this corresponds to only about 6% of global electricity demand and there is a need to increase wind energy penetration in electricity grids. One way to enhance the competitiveness of wind energy is to improve its reliability and availability and reduce associated maintenance costs. This study utilizes a database entitled “Wind Monitor and Evaluation Program (WMEP)” to investigate, model and improve wind turbine reliability and availability. The WMEP database consists of maintenance data of 575 wind turbines in Germany during 1989-2008. It is unique as it includes details of turbine model and size, affected subsystem and component, cause of failure, date and time of maintenance, location, and energy production from the wind turbines. Additional parameters such as climatic regions, geography number of previous failures and mean annual wind speed are added to the database in this study. In this research, two metrics are considered and developed such as time-to-failure or failure rate and time-to-repair or downtime for reliability and availability, respectively. This study investigated failure causes, effects and criticalities of wind turbine subsystems and components, assessed the risk factors impacting wind turbine reliability, modeled the reliability of wind turbines based on assessed risk factors, and predicted the cost of wind turbine failures under various operational and environmental conditions. A well-established reliability assessment technique - Failure Modes, Effects and Criticality Analysis is applied on the WMEP maintenance data from 109 wind turbines and three different climatic regions to understand the impacts of climate and wind turbine design type on wind turbine reliability and availability. First, climatic region impacts on identical wind turbine failures are investigated, then impacts of wind turbine design type are examined for the same climatic region. Furthermore, we compared the results of this investigation with results from previous FMECA studies which neglected impacts of climatic region and turbine design type in section 5.4. Two-step cluster and survival analyses are used to determine risk factors that affect wind turbine reliability. Six operational and environmental factors are considered for this approach, namely capacity factor (CF), wind turbine design type, number of previous failures (NOPF), geographical location, climatic region and mean annual wind speed (MAWS). Data are classified as frequent (time-to-failure80 days) failures and we identified 615 operations listing all these factor and energy production from 21 wind turbines in the WMEP data base. These factors are examined for their impact on wind turbine reliability and results are compared. In addition, wind turbine reliability is modeled by machine learning methods, namely logistic regression (LR) and artificial neural network (ANN), using the considered 615 operations. The objective of this investigation is to model and predict probability of frequently-failing wind turbines based on wind turbines’ known operational and environmental conditions. The models are evaluated and cross validated with 10-fold cross validation and prediction performances and compared with other algorithms such as k-nearest neighbor and support vector machines. Also, prediction performances of LR and ANN are discussed along with their easiness to interpret and share with others. Lastly, using data from 753 operations, a decision support tool for predicting cost of wind turbine failures is developed. The tool development includes machine learning application for estimating probability of failures in 60 days of operation and time-to-repair probabilities for divisions of 0-8hrs, 8-16hrs, 16-24hrs and more than 1 day based on operational and environmental conditions of wind turbines. Prediction for cost of wind turbine failures for 60 days of operation is calculated using assumed costs from time-to-repair divisions. The decision support tool can be updated by the user’s discretion on the cost of failures. This study provides a better understanding of wind turbine failures by investigating associated risk factors, modeling wind turbine reliability and predicting the future cost of failures by applying state-of-the art reliability and data analysis techniques. Wind energy developers and operators can be guided by this study in improving the reliability of wind turbines. Also, wind energy investors, operators and maintenance service managers can predict the cost of wind turbine failures with the decision support tool provided in this study

All-electric LNG a viable alternative to conventional gas turbine driven LNG plant

The world demand for natural gas which is at an increasing trend has rekindled interest in the production and transportation of Liquefied Natural Gas (LNG) from resource rich areas in Africa, Middle East, Far East, Australia and Russia to customers in Europe, Americas, China and India. The challenges for the future are to produce and transport gas in a cost effective manner to be competitive in the market place. Gas is beginning to play an increasingly important role in energy scenario of the world economy. The easiest ways of getting gas to the market is by pipe lines. However to reach markets far and wide across oceans, gas needs to be converted and transported in liquid form. Competitive pressure and search for economies of scale is driving up the size of LNG facilities and hence the capital requirement of each link of the value chain. Interdependent financing of the various links of the value chain, while maintaining their economic viability, is the challenge that sponsors need to address. The industry is potentially a high risk business due to uncertainty associated with the characteristics of the industry, which calls for high level of investment in an environment of volatility of the price and political and economic changes in the world market. LNG production facilities are becoming larger and larger than ever before to take advantage of economies of scale. These massive plants not only have created new challenges in design, procurement and construction and environment but will create new challenges in operation and maintenance. Innovative technologies and first of a kind equipment applications with a rigorous technology development and a stringent testing plans ensure that the facility will achieve a long term reliable operation. Conventional LNG plants use Gas Turbine as main drivers for refrigerant compressors. To this effect All-Electric LNG has a potential to provide an alternative offer a life cycle advantage over the convention. Hence it would be worthwhile to study the pros and cons and prospects offered by this new technology from an overall life cycle perspective for future of LNG projects. This research is an endeavours in this direction